Articles

Page Laubheimer

Page Laubheimer is a former NN/G employee who worked on research, teaching, leadership, and design thought leadership. His expertise focused on web applications, AI, and projects in complex domains. His many research findings and recommendations were also informed by his background in library and information science, and his work often involved information architecture, navigation design, taxonomy construction, and ontology management.

Articles and Videos

  • AI Hallucinations: What Designers Need to Know

    Plausible but incorrect AI responses create design challenges and user distrust. Discover evidence-based UI patterns to help users identify fabrications.

  • Entering the UX Field: How to Overcome the Biggest Challenges

    Entering the UX field can be challenging and daunting. Our roundtable discussion unpacks the most common mistakes and misconceptions of people entering the field and provides actionable advice for how to overcome the biggest challenges.

  • Attitudinal vs. Behavioral Research

    Explore the difference between attitudinal and behavioral UX research. Learn how combining these methods offers a complete view of user interactions and perceptions.

  • Why Use 40 Participants in Quantitative UX Research?

    40 is the optimal sample size for many quantitative UX studies, ensuring a balance of precision, risk, and practicality.

  • How Do Generative AI Systems Work?

    Generative AI systems are prediction machines. This article breaks down neural networks and LLMs in nontechnical language.

  • CASTLE: Measure UX in Workplace Software

    Discover the CASTLE framework for measuring UX in workplace software, an alternative to Google's HEART model.

  • Menu-Design Checklist: 17 UX Guidelines

    People rely on menus to find content and use features. Use this checklist to make sure your menus do their job.

  • Attitudinal vs. Behavioral Research in UX

    Attitudinal research captures user opinions and feelings in the form of self-reported data; behavioral research observes user actions.

  • Tree Testing Part 2: Interpreting the Results

    Analyze tree-testing results including success, first click, and directness to improve information architecture and navigation labels.

  • Personas vs. Analytics Segments

    Avoid creating personas from analytics data alone. Personas are artifacts that aim to capture users' attitudes, goals, and pain points, aspects which analytics alone can't provide.